---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan7
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.85
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilhubert-finetuned-gtzan7

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5569
- Accuracy: 0.85

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 8e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.85  | 4    | 2.2836          | 0.14     |
| 2.2984        | 1.92  | 9    | 2.2574          | 0.18     |
| 2.2856        | 2.99  | 14   | 2.2060          | 0.32     |
| 2.2478        | 3.84  | 18   | 2.1331          | 0.37     |
| 2.1775        | 4.91  | 23   | 1.9859          | 0.47     |
| 2.0557        | 5.97  | 28   | 1.8086          | 0.52     |
| 1.8764        | 6.83  | 32   | 1.6783          | 0.53     |
| 1.7133        | 7.89  | 37   | 1.5235          | 0.54     |
| 1.5661        | 8.96  | 42   | 1.4048          | 0.58     |
| 1.4544        | 9.81  | 46   | 1.3279          | 0.6      |
| 1.3365        | 10.88 | 51   | 1.2591          | 0.67     |
| 1.2228        | 11.95 | 56   | 1.1587          | 0.7      |
| 1.1298        | 12.8  | 60   | 1.1476          | 0.68     |
| 1.0601        | 13.87 | 65   | 1.0066          | 0.77     |
| 0.9886        | 14.93 | 70   | 0.9855          | 0.76     |
| 0.923         | 16.0  | 75   | 0.9767          | 0.73     |
| 0.923         | 16.85 | 79   | 0.8896          | 0.79     |
| 0.8539        | 17.92 | 84   | 0.8421          | 0.78     |
| 0.788         | 18.99 | 89   | 0.8270          | 0.8      |
| 0.7253        | 19.84 | 93   | 0.7764          | 0.82     |
| 0.6523        | 20.91 | 98   | 0.6998          | 0.85     |
| 0.5853        | 21.97 | 103  | 0.6891          | 0.87     |
| 0.5372        | 22.83 | 107  | 0.7106          | 0.8      |
| 0.4815        | 23.89 | 112  | 0.6542          | 0.82     |
| 0.4461        | 24.96 | 117  | 0.6136          | 0.87     |
| 0.3841        | 25.81 | 121  | 0.6338          | 0.81     |
| 0.3505        | 26.88 | 126  | 0.6082          | 0.87     |
| 0.3143        | 27.95 | 131  | 0.5776          | 0.88     |
| 0.2913        | 28.8  | 135  | 0.5833          | 0.86     |
| 0.2519        | 29.87 | 140  | 0.5543          | 0.89     |
| 0.2234        | 30.93 | 145  | 0.5606          | 0.84     |
| 0.1994        | 32.0  | 150  | 0.5726          | 0.86     |
| 0.1994        | 32.85 | 154  | 0.5391          | 0.86     |
| 0.1789        | 33.92 | 159  | 0.5908          | 0.83     |
| 0.1615        | 34.99 | 164  | 0.5498          | 0.85     |
| 0.1444        | 35.84 | 168  | 0.5389          | 0.85     |
| 0.1303        | 36.91 | 173  | 0.5829          | 0.84     |
| 0.1192        | 37.97 | 178  | 0.5278          | 0.87     |
| 0.1074        | 38.83 | 182  | 0.6011          | 0.83     |
| 0.1001        | 39.89 | 187  | 0.5260          | 0.87     |
| 0.0935        | 40.96 | 192  | 0.5778          | 0.84     |
| 0.0885        | 41.81 | 196  | 0.5563          | 0.86     |
| 0.0827        | 42.88 | 201  | 0.5556          | 0.86     |
| 0.0785        | 43.95 | 206  | 0.5807          | 0.84     |
| 0.0767        | 44.8  | 210  | 0.5649          | 0.85     |
| 0.0722        | 45.87 | 215  | 0.5551          | 0.85     |
| 0.0718        | 46.93 | 220  | 0.5432          | 0.86     |
| 0.0701        | 48.0  | 225  | 0.5720          | 0.85     |
| 0.0701        | 48.85 | 229  | 0.5695          | 0.85     |
| 0.068         | 49.92 | 234  | 0.5642          | 0.85     |
| 0.0673        | 50.99 | 239  | 0.5571          | 0.85     |
| 0.0672        | 51.2  | 240  | 0.5569          | 0.85     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3